Abstract
A method to estimate peat depth and extent is vital for accurate estimation of carbon stocks and to facilitate appropriate peatland management. Current methods for direct measurement (e.g. ground penetrating radar, probing) are labour intensive making them unfeasible for capturing spatial information at landscape extents. Attempts to model peat depths using remotely sensed data such as elevation and slope have shown promise but assume a functional relationship between current conditions and gradually accrued peat depth. Herein we combine LiDAR-derived metrics known to influence peat accumulation (elevation, slope, topographic wetness index (TWI)) with passive gamma-ray spectrometric survey data, shown to correlate with peat occurrence, to develop a novel peat depth model for Dartmoor.Total air absorbed dose rates of Thorium, Uranium and Potassium were calculated, referred to as radiometric dose. Relationships between peat depth, radiometric dose, elevation, slope and TWI were trained using 1334 peat depth measurements, a further 445 measurements were used for testing. All variables showed significant relationships with peat depth. Linear stepwise regression of natural log-transformed variables indicated that a radiometric dose and slope model had an r2 = 0.72/0.73 and RMSE 0.31/0.31 m for training/testing respectively. This model estimated an area of 158 ±101 km2 of peaty soil >0.4 m deep across the study area. Much of this area (60 km2) is overlain by grassland and therefore may have been missed if vegetation cover was used to map peat extent. Using published bulk density and carbon content values we estimated 13.1 Mt. C (8.1–21.9 Mt. C) are stored in the peaty soils within the study area. This is an increase on previous estimates due to greater modelled peat depth. The combined use of airborne gamma-ray spectrometric survey and LiDAR data provide a novel, practical and repeatable means to estimate peat depth with no a priori knowledge, at an appropriate resolution (10 m) and extent (406 km2) to facilitate management of entire peatland complexes.
Highlights
The inclusion of wetland drainage and rewetting in the United Nations Framework Convention on Climate Change (2012) has raised renewed interest in mapping peatland extents and depths; to provide better estimates of carbon stocks, monitor changes to peatlands and facilitate appropriate management (Aitkenhead, 2017; Biancalani and Avagyan, 2014)
As blanket peatlands are highly variable in depth (Bragg and Tallis, 2001) there exists an operational challenge to map peat depth at a sufficiently fine spatial resolution to capture the small-scale variability that is known to exist in blanket peat depth over the required spatial extents (m's – km's)
Parry et al (2012) covered a wider range of peat depths and vegetation types, finding peat depths from 0 to 3.30 m, this survey did not cover the central portion of Dartmoor (Fig. 1e) where Harrod (2016) found the deepest peats (7.00 m) (Fig. 1f)
Summary
The inclusion of wetland drainage and rewetting in the United Nations Framework Convention on Climate Change (2012) has raised renewed interest in mapping peatland extents and depths; to provide better estimates of carbon stocks, monitor changes to peatlands and facilitate appropriate management (Aitkenhead, 2017; Biancalani and Avagyan, 2014). As blanket peatlands are highly variable in depth (Bragg and Tallis, 2001) there exists an operational challenge to map peat depth at a sufficiently fine spatial resolution to capture the small-scale variability that is known to exist in blanket peat depth (cm's – m's) over the required spatial extents (m's – km's). The two main methods currently used to measure peat depth are manual probing of the peat in situ and ground-penetrating radar (GPR).
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